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Seasonality and cycles in tourism demand—redux

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  • Vatsa, Puneet

Abstract

Analyzing tourism demand cycles is of strong interest to researchers and forecasters. However, often the preponderance of seasonality encumbers the derivation of cycles that are free of seasonal patterns. Using recent advances in time-series econometrics, we offer a solution. We employ two methods that produce cycles that are robust to seasonal properties of the data; cycles from seasonally adjusted and unadjusted data are virtually indistinguishable.

Suggested Citation

  • Vatsa, Puneet, 2021. "Seasonality and cycles in tourism demand—redux," Annals of Tourism Research, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:anture:v:90:y:2021:i:c:s0160738320302498
    DOI: 10.1016/j.annals.2020.103105
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    References listed on IDEAS

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    1. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
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    4. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    5. Vatsa, Puneet, 2020. "Comovement amongst the demand for New Zealand tourism," Annals of Tourism Research, Elsevier, vol. 83(C).
    6. Chan, Felix & Lim, Christine, 2011. "Spectral analysis of seasonality in tourism demand," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1409-1418.
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    1. Jing Zhang & Zhonglei Yu & Changhong Miao & Yuting Li & Shuai Qiao, 2022. "Cultural Tourism Weakens Seasonality: Empirical Analysis of Chinese Tourism Cities," Land, MDPI, vol. 11(2), pages 1-14, February.

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